Sure. It's open chinese poker:  
http://www.pokerlistings.com/poker-rules-chinese-poker


Среда, 12 июня 2013, 20:57 +01:00 от Nick Wedd <[email protected]>:
>On 12/06/2013 20:33, Oleg Barmin wrote:
>>  > For quality assessment, play many games against one or more reference
>> opponents.
>> It's difficult to assament algorithm with a game against humans. The
>> game is young and there are no recognized masters at the moment. So it's
>> very hard to find human-opponent with a really good game skills.
>>
>>  >  With card games you can get some serious intransitivity,  rocks,
>> paper, scissors type of stuff.
>> The aim of this game is to max your scores. Each turn you need to select
>> one of three choices. Each choice has an expectation value of your
>> scores. Optimal strategy here is to select a choice with max expectation
>> value. But it will take a years to calculate an expectation value at the
>> start of the game. So the game has no such intransitivity as rocks,
>> paper, scissors.
>> At the last turns we can make a complete choice enumeration and
>> calculate an exact scores expectation value ( does go algorithms use the
>> same technique? ) . It's not the way for the first half of the game. But
>> the first half is more important.
>
>Can you give a link to the rules of this game?  Or even just tell us its 
>name?
>
>Nick
>
>>
>> Oleg
>>
>>
>> Среда, 12 июня 2013, 14:24 -04:00 от Don Dailey < [email protected] >:
>>
>>
>>
>>     On Wed, Jun 12, 2013 at 11:30 AM, David Fotland
>>     < [email protected]
>>     <sentmsg?mailto=mailto%3afotland@smart%2dgames.com>> wrote:
>>
>>         For quality assessment, play many games against one or more
>>         reference opponents.
>>
>>
>>     Especially for a game that is not a game of perfect information such
>>     as go or chess.   With card games you can get some serious
>>     intransitivity,  rocks, paper, scissors type of stuff.
>>
>>     Don
>>
>>
>>         ____
>>
>>         __ __
>>
>>         David____
>>
>>         __ __
>>
>>         *From: *[email protected]
>>         < sentmsg?mailto=mailto%3acomputer%2dgo%[email protected] >
>>         [mailto: [email protected]
>>         < sentmsg?mailto=mailto%3acomputer%2dgo%[email protected] >]
>>         *On Behalf Of *Oleg Barmin
>>         *Sent:* Wednesday, June 12, 2013 8:02 AM
>>         *To:*  [email protected]
>>         < sentmsg?mailto=mailto%3acomputer%[email protected] >
>>         *Subject:* [Computer-go] algorithm quality assessment____
>>
>>         __ __
>>
>>         Hi, everybody,____
>>
>>         I am working at the development of a cards game algorithm using
>>         MCTS. Technically, the game model is expect minmax tree search,
>>         where direct search takes up too much time, that is why I
>>         decided to use MCTS.____
>>
>>         The issue of using MCST, like any other approximation algorithm
>>         is its quality assessment. I am developing an algorithm for a
>>         game where no recognized masters exist. How do you think, guys,
>>         if for instance Go (or Amazons) provided no way to assess an
>>         algorithm playing with professional gamers (or other programs),
>>         how would you assets its quality?____
>>
>>         My second question: I have not yet learned Go in and out,
>>         however in my opinion, any search of a next step should identify
>>         a number of options with similar or even the same assessment.
>>         How do you resolve this issue?____
>>
>>
>>         Best regards,
>>         Oleg Barmin.____
>>
>>
>>         _______________________________________________
>>         Computer-go mailing list
>>  [email protected]
>>         < sentmsg?mailto=mailto%3acomputer%[email protected] >
>>  http://dvandva.org/cgi-bin/mailman/listinfo/computer-go
>>
>>
>>
>>
>> Best regards,
>> Oleg Barmin.
>>
>>
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>
>
>-- 
>Nick Wedd
>[email protected]
>_______________________________________________
>Computer-go mailing list
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Best regards,
Oleg Barmin.
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